Kaufmann Joshua, Bhovad Priyanka, Li Suyi
Department of Mechanical Engineering, Clemson University, Clemson, South Carolina, USA.
Soft Robot. 2022 Apr;9(2):212-223. doi: 10.1089/soro.2020.0075. Epub 2021 Feb 26.
This study examines a biology-inspired approach of using reconfigurable articulation to reduce the control requirement for soft robotic arms. We construct a robotic arm by assembling Kresling origami modules that exhibit predictable bistability. By switching between their two stable states, these origami modules can behave either like a flexible joint with low bending stiffness or like a stiff link with high stiffness, without requiring any continuous power supply. In this way, the robotic arm can exhibit pseudo-linkage kinematics with lower control requirements and improved motion accuracy. A unique advantage of using origami as the robotic arm skeleton is that its bending stiffness ratio between stable states is directly related to the underlying Kresling design. Therefore, we conduct extensive parametric analyses and experimental validations to identify the optimized Kresling pattern for articulation. The results indicate that a higher angle ratio, a smaller resting length at contracted stable state, and a large number of polygon sides can offer more significant and robust bending stiffness tuning. Based on this insight, we construct a proof-of-concept, tendon-driven robotic arm consisting of three modules and show that it can exhibit the desired reconfigurable articulation behavior. Moreover, the deformations of this manipulator are consistent with kinematic model predictions, which validate the possibility of using simple controllers for such compliant robotic systems.
本研究探讨了一种受生物学启发的方法,即利用可重构关节来降低对软机器人手臂的控制要求。我们通过组装具有可预测双稳态的克雷斯林折纸模块构建了一个机器人手臂。通过在其两个稳定状态之间切换,这些折纸模块既可以表现得像具有低弯曲刚度的柔性关节,也可以表现得像具有高刚度的刚性连杆,而无需任何连续电源。通过这种方式,机器人手臂可以展现出具有较低控制要求和更高运动精度的伪连杆运动学。将折纸用作机器人手臂骨架的一个独特优势在于,其稳定状态之间的弯曲刚度比与基础的克雷斯林设计直接相关。因此,我们进行了广泛的参数分析和实验验证,以确定用于关节的优化克雷斯林图案。结果表明,更高的角度比、收缩稳定状态下更小的静止长度以及大量的多边形边可以提供更显著且稳健的弯曲刚度调整。基于这一见解,我们构建了一个由三个模块组成的概念验证肌腱驱动机器人手臂,并表明它可以展现出所需的可重构关节行为。此外,该操纵器的变形与运动学模型预测一致,这验证了为此类柔顺机器人系统使用简单控制器的可能性。